148ced9ebb5275c6e11baba5befd075e26bb428f,src/model.py,DRIT,resume,#DRIT#,388

Before Change

    // optimizer
    self.disA_opt.load_state_dict(checkpoint["disA_opt"])
    self.disA2_opt.load_state_dict(checkpoint["disA2_opt"])
    self.disB_opt.load_state_dict(checkpoint["disB_opt"])
    self.disB2_opt.load_state_dict(checkpoint["disB2_opt"])
    self.disContent_opt.load_state_dict(checkpoint["disContent_opt"])
    self.enc_c_opt.load_state_dict(checkpoint["enc_c_opt"])
    self.enc_a_opt.load_state_dict(checkpoint["enc_a_opt"])
    self.gen_opt.load_state_dict(checkpoint["gen_opt"])
    return checkpoint["ep"], checkpoint["total_it"]

  def save(self, filename, ep, total_it):

After Change

    self.enc_a.load_state_dict(checkpoint["enc_a"])
    self.gen.load_state_dict(checkpoint["gen"])
    // optimizer
    if train:
      self.disA_opt.load_state_dict(checkpoint["disA_opt"])
      self.disA2_opt.load_state_dict(checkpoint["disA2_opt"])
      self.disB_opt.load_state_dict(checkpoint["disB_opt"])
      self.disB2_opt.load_state_dict(checkpoint["disB2_opt"])
      self.disContent_opt.load_state_dict(checkpoint["disContent_opt"])
      self.enc_c_opt.load_state_dict(checkpoint["enc_c_opt"])
      self.enc_a_opt.load_state_dict(checkpoint["enc_a_opt"])
      self.gen_opt.load_state_dict(checkpoint["gen_opt"])
    return checkpoint["ep"], checkpoint["total_it"]

  def save(self, filename, ep, total_it):
    state = {

Instances